Journal article
Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model
Atmospheric environment (1994), Vol.45(16), pp.2769-2780
2011
DOI: 10.1016/j.atmosenv.2011.02.001
Abstract
This study presents a system to predict high pollution events that develop in connection with enhanced subsidence due to coastal lows, particularly in winter over Santiago de Chile. An accurate forecast of these episodes is of interest since the local government is entitled by law to take actions in advance to prevent public exposure to PM10 concentrations in excess of 150 μg m
−3 (24 h running averages). The forecasting system is based on accurately simulating carbon monoxide (CO) as a PM10/PM2.5 surrogate, since during episodes and within the city there is a high correlation (over 0.95) among these pollutants. Thus, by accurately forecasting CO, which behaves closely to a tracer on this scale, a PM estimate can be made without involving aerosol-chemistry modeling. Nevertheless, the very stable nocturnal conditions over steep topography associated with maxima in concentrations are hard to represent in models. Here we propose a forecast system based on the WRF–Chem model with optimum settings, determined through extensive testing, that best describe both meteorological and air quality available measurements. Some of the important configurations choices involve the boundary layer (PBL) scheme, model grid resolution (both vertical and horizontal), meteorological initial and boundary conditions and spatial and temporal distribution of the emissions. A forecast for the 2008 winter is performed showing that this forecasting system is able to perform similarly to the authority decision for PM10 and better than persistence when forecasting PM10 and PM2.5 high pollution episodes. Problems regarding false alarm predictions could be related to different uncertainties in the model such as day to day emission variability, inability of the model to completely resolve the complex topography and inaccuracy in meteorological initial and boundary conditions. Finally, according to our simulations, emissions from previous days dominate episode concentrations, which highlights the need for 48 h forecasts that can be achieved by the system presented here. This is in fact the largest advantage of the proposed system.
► An urban scale PM10 and PM2.5 forecasting system is presented and evaluated. ► The system tackles the stable nocturnal conditions and steep topography. ► PM10 and PM2.5 events are effectively simulated using CO as a PM surrogate. ► Great sensitivity to PBL scheme, grid resolution, boundary conditions and emissions. ► Pollution episodes seem to be dominated by previous days emissions.
Details
- Title: Subtitle
- Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model
- Creators
- Pablo E Saide - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA, USAGregory R Carmichael - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA, USAScott N Spak - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA, USALaura Gallardo - Departamento de Geofísica, Universidad de Chile, Santiago, ChileAxel E Osses - Centro de Modelamiento Matemático, UMI 2807, Universidad de Chile-CNRS, Santiago, ChileMarcelo A Mena-Carrasco - Center for Sustainability Research, Universidad Andrés Bello, Santiago, ChileMariusz Pagowski - NOAA Earth System Research Laboratory, Boulder, CO, USA
- Resource Type
- Journal article
- Publication Details
- Atmospheric environment (1994), Vol.45(16), pp.2769-2780
- DOI
- 10.1016/j.atmosenv.2011.02.001
- ISSN
- 1352-2310
- eISSN
- 1873-2844
- Publisher
- Elsevier Ltd
- Language
- English
- Date published
- 2011
- Academic Unit
- Civil and Environmental Engineering; Center for Global & Regional Environmental Research; Nursing; Public Policy Center (Archive); Chemical and Biochemical Engineering; School of Planning and Public Affairs
- Record Identifier
- 9983992003502771
Metrics
22 Record Views